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Metal-organic cages (MOCs) have garnered significant attention due to their unique discrete structures, intrinsic porosity, designability, and tailorability. However, weak inter-cage interactions, such as van der Waals forces and hydrogen bonding can cause solid-state MOCs to lose structural integrity during desolvation, leading to the loss of porosity. In this work, a novel strategy to retain the permanent porosity of Cu-paddlewheel-based MOCs, enabling their use as heterogeneous catalysts is presented. Post-synthetic solvothermal treatments in non-coordinating solvents, mesitylene, and p-xylene, effectively preserve the packing structures of solvent-evacuated MOCs while preventing cage agglomeration. The resulting MOCs exhibit an exceptional N2 sorption capacity, with a high surface area (SBET = 1934 m2 g-1 for MOP-23), which is among the highest reported for porous MOCs. Intriguingly, while the solvothermal treatment reduced Cu(II) to Cu(I) in the Cu-paddlewheel clusters, the MOCs with mixed-valenced Cu(I)/Cu(II) maintained their crystallinity and permanent porosity. The catalytic activities of these MOCs are successfully examined in copper(I)-catalyzed hydrative amide synthesis, highlighting the prospect of MOCs as versatile reaction platforms.
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An unprecedented correlation between the catalytic activity of a Zr-based UiO-type metal-organic framework (MOF) and its degree of interpenetration (DOI) is reported. The DOI of an MOF is hard to control owing to the high-energy penalty required to construct a partially interpenetrated structure. Surprisingly, strong interactions between building blocks (inter-ligand hydrogen bonding) facilitate the formation of partially interpenetrated structures under carefully regulated synthesis conditions. Moreover, catalytic conversion rates for cyanosilylation and Knoevenagel condensation reactions are found to be proportional to the DOI of the MOF. Among MOFs with DOIs in the 0-100% range, that with a DOI of 87% is the most catalytically active. Framework interpenetration is known to lower catalytic performance by impeding reactant diffusion. A higher effective reactant concentration due to tight inclusion in the interpenetrated region is possibly responsible for this inverted result.
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Silicene, a graphene-like 2D material made from Si atoms, has been fabricated and studied for its promising applications in micro/nanoelectronics. For the reliable function of silicene devices, it is important to investigate silicene's mechanical properties. In this study, the authors conducted density functional theory (DFT) simulations of mechanical tests of silicene and investigated the elastic modulus and mechanical response such as structural transformation. In addition, the authors optimized the Tersoff potential parameters using a gradient-based minimization with a grid search method in hyperdimensional parameter space, to match the DFT calculation results in the elastic regime. With the new parameter set, the elastic moduli of silicene in the zigzag (ZZ) and armchair (AC) directions were computed with molecular statics (MS) simulations and compared with those of other Si interatomic potential models and DFT results. In addition, uniaxial tensile tests along the ZZ and AC directions were performed to examine how far the Tersoff model is transferable with our new parameter set to describe the nonlinear mechanical behavior of silicene. The results of uniaxial tensile tests suggest that the angle penalty function in the Tersoff model needs to be modified and that the stress-strain curve predicted with this modification shows improvement compared to the original function.
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We report the dual postsynthetic modification (PSM) of a metal-organic framework (MOF) involving the microscopic conversion of C-H bonds into C-C bonds and the mesoscopic introduction of hierarchical porosity. MOF crystals underwent single-crystal-to-single-crystal transformations during the electrophilic aromatic substitution of Co2 (m-DOBDC) (m-DOBDC4- =4,6-dioxo-1,3-benzenedicarboxylate) with alkyl halides and formaldehyde. The steric hindrance caused by the proximity of the introduced functional groups to the coordination bonds reduced bond stability and facilitated the transformation into hierarchically porous mesostructures by etching with in situ generated protons (hydroniums) and halides. The numerous defect sites in the mesostructural MOFs are potential water-sorption sites. However, since the introduced functional groups are close to the main adsorption sites, even methyl groups are able to considerably decrease water adsorption, whereas hydroxy groups increase adsorption at low vapor pressures.
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In this study, we report the crystallinity effects of submicrometer titanium dioxide (TiO2) nanotube (TNT) incorporated with silver (Ag) nanoparticles (NPs) on surface-enhanced Raman scattering (SERS) sensitivity. Furthermore, we demonstrate the SERS behaviors dependent on the plasmonic-photonic interference coupling (P-PIC) in the TNT-AgNP nanoarchitectures. Amorphous TNTs (A-TNTs) are synthesized through a two-step anodization on titanium (Ti) substrate, and crystalline TNTs (C-TNTs) are then prepared by using thermal annealing process at 500 °C in air. After thermally evaporating 20 nm thick Ag on TNTs, we investigate SERS signals according to the crystallinity and P-PIC on our TNT-AgNP nanostructures. (A-TNTs)-AgNP substrates show dramatically enhanced SERS performance as compared to (C-TNTs)-AgNP substrates. We attribute the high enhancement on (A-TNTs)-AgNP substrates with electron confinement at the interface between A-TNTs and AgNPs as due to the high interfacial barrier resistance caused by band edge positions. Moreover, the TNT length variation in (A-TNTs)-AgNP nanostructures results in different constructive or destructive interference patterns, which in turn affects the P-PIC. Finally, we could understand the significant dependency of SERS intensity on P-PIC in (A-TNTs)-AgNP nanostructures. Our results thus might provide a suitable design for a myriad of applications of enhanced EM on plasmonic-integrated devices.
RESUMO
Given the growing concern over the deployment of toxic chemicals in warfare, the rapid and accurate removal and detection of cyanogen chloride (CK) as a blood agent has become increasingly critical. However, conventional physisorbents and chemisorbents used in military respirators are insufficient for the effective removal of CK. In this study, we demonstrate the chemisorption and sensing abilities of Co2(m-DOBDC) (m-DOBDC4- = 4,6-dioxo-1,3-benzenedicarboxylate) for CK via electrophilic aromatic substitution (EAS) in humid environments. Unlike the chemisorption in triethylenediamine (TEDA) impregnated carbon materials, which generates by-products through hydrolysis, the electron-rich C5 sites in m-DOBDC4- ligands give rise to cyano substitution with CK. This leads to the formation of stable C-C bonds and chloride ions (Cl-) coordinating with open Co2+ sites. Such a mechanism prevents the generation of toxic by-products like cyanic acid and hydrochloric acid. Breakthrough experiments conducted in a packed-bed system conclusively demonstrated the superior CK removal capacity of Co2(m-DOBDC) (1662 min/g), compared to TEDA-impregnated activated carbon (323 min/g) under humid conditions. Considering that MOF-74 series, isostructural with Co2(m-DOBDC), barely adsorb CK under similar conditions, this finding marks a significant advancement in developing novel sorbents for CK removal. Moreover, this chemisorption not only exhibited rapid and highly efficient CK removal but also enabled colorimetric monitoring via the distinctive color change induced by the coordination of Cl- acting as σ donors. These findings facilitate the development of adsorption and sensing equipment to protect military personnel from toxic chemical threats.
Assuntos
Colorimetria , Estruturas Metalorgânicas , Nitrilas , Adsorção , Estruturas Metalorgânicas/química , Nitrilas/química , Nitrilas/análise , Cianetos/análise , Cianetos/químicaRESUMO
We compared the prediction performance of machine learning-based undiagnosed diabetes prediction models with that of traditional statistics-based prediction models. We used the 2014-2020 Korean National Health and Nutrition Examination Survey (KNHANES) (N = 32,827). The KNHANES 2014-2018 data were used as training and internal validation sets and the 2019-2020 data as external validation sets. The receiver operating characteristic curve area under the curve (AUC) was used to compare the prediction performance of the machine learning-based and the traditional statistics-based prediction models. Using sex, age, resting heart rate, and waist circumference as features, the machine learning-based model showed a higher AUC (0.788 vs. 0.740) than that of the traditional statistical-based prediction model. Using sex, age, waist circumference, family history of diabetes, hypertension, alcohol consumption, and smoking status as features, the machine learning-based prediction model showed a higher AUC (0.802 vs. 0.759) than the traditional statistical-based prediction model. The machine learning-based prediction model using features for maximum prediction performance showed a higher AUC (0.819 vs. 0.765) than the traditional statistical-based prediction model. Machine learning-based prediction models using anthropometric and lifestyle measurements may outperform the traditional statistics-based prediction models in predicting undiagnosed diabetes.
Assuntos
Diabetes Mellitus , Humanos , Inquéritos Nutricionais , Diabetes Mellitus/diagnóstico , Diabetes Mellitus/epidemiologia , Aprendizado de Máquina , Modelos Estatísticos , Curva ROCRESUMO
The ability to chemisorb iodine is important for the safe long-term storage of fission products from nuclear reactors. Herein, we successfully used single-crystal X-ray diffraction analysis to crystallographically visualize I2 binding sites in two isostructural metal-organic frameworks, viz. Co2(m-DOBDC) (m-DOBDC4- = 4,6-dioxo-1,3-benzenedicarboxylate) and Co2(p-DOBDC) (p-DOBDC4- = 2,5-dioxo-1,4-benzenedicarboxylate), with increasing I2 loading. Interestingly, the C-H bond at the electron-rich carbon (C5) of m-DOBDC4- is activated toward electrophilic aromatic substitution, forming an aryl C-I bond and I- or I3- that coordinates to unsaturated open Co sites. Cooperation between the ligand and the open Co sites leads to rapid chemisorption of I2 even under mild adsorption conditions, such as room temperature. In contrast, molecular I2 coordinates to the open Co sites of Co2(p-DOBDC). Owing to the chemisorption of I2, I2@Co2(m-DOBDC) decomposes at a much higher temperature than I2@Co2(p-DOBDC), as revealed by thermogravimetric analysis.
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Local order of liquid Ti is studied by ab initio molecular dynamics to address the unique liquid structure factor in experiments reported recently. The present study reveals that the local order of liquid Ti is in the form of fragments of the distorted icosahedral short range order, where the distortion is induced by strong bond order effects. We show that the fragments in the short-bond rich region separated from the background liquid account for the pronounced feature in structure factor of liquid Ti.
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Liquid-liquid transitions under high pressure are found in many elemental materials, but the transitions are known to be associated with either sp-valent materials or f-valent rare-earth elements, in which the maximum or a negative slope in the melting line is readily suggestive of the transition. Here we find a liquid-liquid transition with a positive melting slope in transition metal Ti from structural, electronic, and thermodynamic studies using ab-initio molecular dynamics calculations, showing diffusion anomaly, but no density anomaly. The origin of the transition in liquid Ti is a pressure-induced increase of local structures containing very short bonds with directionality in electronic configurations. This behavior appears to be characteristic of the early transition metals. In contrast, the late transition metal liquid Ni does not show the L-L transition with pressure. This result suggests that the possibility of the L-L transition decreases from early to late transition metals as electronic structures of late transition metals barely have a Jahn-Teller effect and bond directionality. Our results generalize that a phase transition in disordered materials is found with any valence band regardless of the sign of the melting slope, but related to the symmetry of electronic structures of constituent elements.
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Recently it has been suggested theoretically and discovered experimentally that pressure can induce body-centered cubic vanadium to transition to a rhombohedral phase. Here we show using density functional theory calculations that alloying can affect the same transition, and in particular alloying can increase the stability of the rhombohedral phase, reducing the pressure needed to induce the transition. These calculations are full supercell calculations, as opposed to the virtual crystal approximation and other approximate schemes that neglect atomic relaxation and local bonding effects. These results suggest a way in which alloying provides a means of designing this class of exotic phases to be more robust.
RESUMO
Icosahedral clusters in Ti and Ni are studied with first-principles density functional calculations. We find significant distortion on the Ti icosahedron caused by the strong interaction between surface atoms on the icosahedron but not between the center atom and surface atoms, whereas no such distortion is observed on Ni clusters. In addition, distortion becomes more severe when atoms are added to the Ti(13) cluster resulting in short bonds. Such distorted icosahedra having short bonds are essential in explaining the structure factor of Ti liquid obtained in experiment.